The present invention relates to an image sensor comprised of an array of detecting cells for detecting images. Specifically, the image sensor is capable of extracting edges of detected images and determining the orientations (tangential directions) of edge points of the detected images.
2. Description of Prior Art
Pattern recognition is a technical field in which a machine is designed to be capable of visually perceiving objects as human eyes. Present pattern recognition machines customarily employ CCD (Charge Coupled Device) or CID (Charge Injection Device) for detecting photons reflected from objects and incident thereupon and generating thereby electrical signals representing analog image signals. The thus generated analog image signals are subsequently converted into digital image signals by means of analog-to-digital converters. The digital image signals can then be processed by general purpose computer systems running pattern recognition softwares for analysis of the image pattern.
Although present computer systems are provided with very high processing speed, pattern recognition speed thereof is still far behind that achieved by human visual nerves. It is therefore the purpose of recent research programs directed on developments of neural network systems, in which electronic circuits are arranged to process signals in a way that resembles functions performed by human visual nerve cells.
According to studies in neurophysiology, when an image is projected upon the retina of a human eye, the human visual neurons for the first step perform a function of extracting the edges of the visualized image and then the brain neurons for the next step perform a function of determining orientations, i.e. tangential directions, of all edge points of the visualized image. In other words, signals concerning locations and orientations of edge points of the visualized image are firstly generated by the human visual neurons for subsequent processing by the human brain. A reference to the details of these functions can be made to a book "From Neuron to Brain", 2nd Ed , co-authored by S. W. Kuffler, J. G. Nicholls, and A. R. Martin, and published by Sinauer, Sunderland, Mass., 1984.
Consequently, to simulate these functions performed by the human retina and brain, a pattern recognition machine must be able to determine locations and orientations of the edge points of a detected image. A pioneer work on this technical field has been conducted by Dr. Carver Mead of California Institute of Technology. A reference to the work of Dr. Mead can be made to one of his textbook entitled "Analog VLSI and Neural Systems", published by Addison Wesley, Reading, Mass., 1989.
Furthermore, Wen-Jyh Sah et al. of Department of Electrical Engineering at National Taiwan University, who are also the inventors of the present invention, have developed an image sensor comprised of an array of photodetecting cells having specially shaped photo-sensitive surfaces. Each photo-detecting cell is technically dubbed as "a four-quadrant orientation detector (FOQUOD)". The work of Sah et al. has been published in a technical paper entitled "Amorphous Silicon Four Quadrant Orientation Detector (FOQUOD) for Application to Neural Network Image Sensors" on TECHNICAL DIGEST of the 1990 IEDM, pp. 291-294, 1990. A brief description of the FOQUOD will be made hereinunder with references made to FIGS. 1-7.
Referring to FIGS. 1-2, a pattern recognition system is configured by utilizing an image sensor 2 consisting of a 16.times.16 array of FOQUODs. A camera lens (not shown) is customarily used to focus images of objects onto the image sensor 2. One FOQUOD corresponds to one pixel in the converted digital image. As shown more clearly in FIG. 2, an individual FOQUOD consists of four photo-diodes having their photo-sensitive surfaces formed in the shape of a right triangle with equilateral sides. Functions of the thus formed four photo-sensitive surfaces are described in the aforementioned technical paper.
A scanning circuit 20 is used in combination with a pair of multi-plexers 21, 22 to select at a time one of the output currents I.sub.1 -I.sub.3 and I.sub.2 -.sub.4 of the FOQUODs. An analog-to-digital converters (A/D) 31, which is embodied by using a Keithley 485 picoammeter, is used to convert the output currents I.sub.1 -I.sub.3 and I.sub.2 -.sub.4 to binary signals. The binary signals are processed further by a computer 40 to determine if an edge segment falls upon the FOQUOD being selected and further determine the orientation of the image edge segment.
Physically, an image edge is a borderline between an illuminated region and a non-illuminated region. Since the FOQUOD is small in size, an image edge segment that falls upon one individual FOQUOD can be substantially regarded as a straight line segment.
It is assumed that a 2-D rectangular coordinate system having an X-axis and a Y-axis is imposed onto the plane on which the image sensor 2 is disposed. The orientation of an image edge segment detected by one FOQUOD is therefore defined as the slope of the image edge segment in the rectangular coordinate system. In rectangular coordinate system, the slope of a line is defined in general as being equal to tan(.THETA.), where .THETA. is a polar angle of the line with respective to the X-axis.
Referring to FIG. 3, when the FOQUOD is practically implemented on a semiconductor chip, there are two crossed strips of non-photosensitive region provided to separate the four photo-sensitive surfaces from each other. The side length of the FOQUOD is designated by w and a length left at both ends of each side for the non-photosensitive region is designated by t.
Referring to FIG. 4, an image edge represented by a line L is shown, which passes through the center point O of the FOQUOD and is oriented with an angle .THETA. with respect to the X-axis. It has been found that when the angle .THETA. is proximate 45.degree. or 135.degree., i.e. the image edge is substantially in coincidence with one of the strips of non-photosensitive region, the area of illuminated portions of the non-photosensitive region is comparable to the area of illuminated portions of the photo-sensitive surfaces of the FOQUOD. Consequently, a detected orientation error between the detected orientation determined by the computer 40 and the actual orientation is larger in this case.
A first theoretical simulation is therefore conducted to find the effect of the non-photosensitive region on the detected orientation error, in which the line L is rotated about the center point O of the FOQUOD from .THETA.=0.degree. to .THETA.=90.degree. with a predetermined increment and at each angle .THETA. the detected orientation .THETA..sub.m is calculated in accordance with the areas of the presumed "illuminated portions" to the right of the line L. The simulation is carried out by a computer program. Three samples of FOQUOD are sketched and input to the computer program for the simulation, each with a different width for the non-photosensitive region thereof, i.e.
t/w=0,025, PA1 t/w=0.05, and PA1 t/w=0.15
respectively. The results for the three FOQUOD samples are plotted in a graph shown in FIG. 5, wherein the abscissa represents orientations of the line L rotated from .THETA.=0.degree. to .THETA.=90.degree. and the ordinate represents errors between calculated orientations .THETA..sub.m and actual orientation .THETA.. It can be seen from the graph of FIG. 5 that the plot corresponding to t/w=0.025 varies leasts about an axis representing zero detected orientation error. Accordingly, it is found that a smaller t for the width of the non-photosensitive region will result in lower detected orientation errors.
Referring to FIG. 6, a second simulation is conducted to see how detected orientation error .THETA..sub.m -.THETA..sub.a is related to the width of the non-photosensitive region with respect to image edges having a same orientation but falling upon different segments of the FOQUOD. In the second simulation, the orientation of the line L is fixed at .THETA..sub.a =55.5.degree. and the line L is shifted horizontally along the X-axis to different positions. A reference axis Z having arbitrarily marked units is sketched to indicate positions of the line L, in which Z=.+-.9 are where the line L shifts to boundary positions intersecting vertices of the FOQUOD and Z=0 is where the line L passes through the center point O of the FOQUOD. The line L shifts from the position Z=-9 to the position Z=9 with a predetermined increment and at each position Z the detected orientation .THETA..sub.m is calculated in accordance with the areas of the presumed "illuminated portions" to the right of the line L. The simulation is carried out three times with the same three FOQUOD samples used in the first simulation. The results are plotted in a graph shown in FIG. 7, wherein the abscissa represents the position of the line L shifted from Z=-9 to Z=9 and the ordinate represents errors between the calculated orientation .THETA..sub.m and .THETA..sub.a. It can be seen from the graph of FIG. 7 that the plot corresponding to t/w=0.025 varies leasts about an axis representing zero detected orientation error.
As revealed by the results of the foregoing two simulations, performance of the FOQUOD can be enhanced by decreasing the ratio t/w, in other words, by decreasing the width of the non-photosensitive region. However, due to limited capability in fabrication technology, there exist a minimum width achievable for the non-photosensitive region. Consequently, when the size of FOQUOD is intended to be made smaller to incorporate more FOQUODs in a single chip, only the side length of the FOQUOD and not the width of the non-photosensitive region can be further reduced. Therefore, further decreasing w will only result in an increase of the ratio t/w. Incorporating denser FOQUODs in a single chip is therefore restricted. Research effort has been therefore undertaken for an improvement on the FOQUOD so that performance would be as good with a larger t/w ratio.